| 我国大陆强震预测的支持向量机方法 |
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| 引用本文： | 王炜,刘悦,李国正,吴耿锋,马钦忠,赵利飞,林命週.我国大陆强震预测的支持向量机方法[J].地震学报,2006,28(1):29-36. |
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| 作者姓名： | 王炜 刘悦 李国正 吴耿锋 马钦忠 赵利飞 林命週 |
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| 作者单位： | 1） 中国上海 200062上海市地震局2） 中国上海 200072上海大学计算机工程与科学学院 |
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| 基金项目： | 地震科学联合基金(104090)资助. |
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| 摘 要： | 统计学习理论是研究小样本情况下机器学习规律的理论. 支持向量机是基于统计学习理论框架下的一种新的通用机器学习方法. 它不但较好地解决了以往困扰很多学习方法的小样本、过学习、高维数、局部最小等实际难题，而且具有很强的泛化（预测）能力，其预测效果通常优于人工神经网络. 我国大陆强震与全球主要板块边界的强震活动之间具有一定的关系，但是这种关系具有较强的非线性. 尽管这种关系还不清楚， 但是通过支持向量机可以很好地进行建模， 并对我国大陆强震进行预测.
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| 关 键 词： | 统计学习理论 支持向量机 人工神经网络 地震形势 |
| 文章编号： | 0253-3782(2006)01-0029-08 |
| 修稿时间： | 2005年5月8日 |
SUPPORT VECTOR MACHINE METHOD FOR FORECASTING FUTURE STRONG EARTHQUAKES IN CHINESE MAINLAND |
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| Wang Wei,Liu Yue,Li Guozheng,Wu Gengfeng,Ma Qinzhong,Zhao Lifei,Lin Mingzhou.SUPPORT VECTOR MACHINE METHOD FOR FORECASTING FUTURE STRONG EARTHQUAKES IN CHINESE MAINLAND[J].Acta Seismologica Sinica,2006,28(1):29-36. |
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| Authors: | Wang Wei Liu Yue Li Guozheng Wu Gengfeng Ma Qinzhong Zhao Lifei Lin Mingzhou |
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| Abstract: | Statistical learning theory is for small-sample statistics. And support vector machine is a new machine learning method based on the statistical learning theory. The support vector machine not only has solved certain problems in many learning methods, such as small sample, over fitting, high dimension and local minimum, but also has a high generalization (forecasting) ability than that of artificial neural networks. The strong earthquakes in Chinese mainland are related to a certain extent to the intensive seismicity along the main plate boundaries in the world; however, the relation is nonlinear. In the paper, we have studied this unclear relation by the support vector machine method for the purpose of forecasting strong earthquakes in the Chinese mainland. |
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| Keywords: | statistical learning theory support vector machine artificial neural networks earthquake situation |
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